Matching Stochastic Algorithms to Objective Function Landscapes

There are no files associated with this record.

Title Matching Stochastic Algorithms to Objective Function Landscapes
Author Baritompa, W. P.; Dur, M.; Hendrix, E.M.T.; Noakes, L.; Pullan, Wayne John; Wood, G.R.
Journal Name Journal of Global Optimization
Editor P.M. Pardalos
Year Published 2005
Place of publication Netherlands
Publisher Springer
Abstract Large scale optimisation problems are frequently solved using stochastic methods. Such methods often generate points randomly in a search region in a neighbourhood of the current point, backtrack to get past barriers and employ a local optimiser. The aim of this paper is to explore how these algorithmic components should be used, given a particular objective function landscape. In a nutshell, we begin to provide rules for efficient travel, if we have some knowledge of the large or small scale geometry.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/s10898-004-9968-y
Volume 31
Issue Number 4
Page from 579
Page to 598
ISSN 0925-5001
Date Accessioned 2006-02-23
Language en_AU
Faculty Faculty of Engineering and Information Technology
Subject PRE2009-Optimisation
URI http://hdl.handle.net/10072/4283
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

Show simple item record

Griffith University copyright notice